Health services research into postnatal depression: results from a preliminary cross-cultural study
Bibliographic record
Abstract
BACKGROUND: Little is known about the availability and uptake of health and welfare services by women with postnatal depression in different countries. AIMS: Within the context of a cross-cultural research study, to develop and test methods for undertaking quantitative health services research in postnatal depression. METHOD: Interviews with service planners and the collation of key health indicators were used to obtain a profile of service availability and provision. A service use questionnaire was developed and administered to a pilot sample in a number of European study centres. RESULTS: Marked differences in service access and use were observed between the centres, including postnatal nursing care and contacts with primary care services. Rates of use of specialist services were generally low. Common barriers to access to care included perceived service quality and responsiveness. On the basis of the pilot work, a postnatal depression version of the Service Receipt Inventory was revised and finalised. CONCLUSIONS: This preliminary study demonstrated the methodological feasibility of describing and quantifying service use, highlighted the varied and often limited use of care in this population, and indicated the need for an improved understanding of the resource needs and implications of postnatal depression.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".